Welcome to the Quantum Realm.

Enjoy today’s breakdown of news, research, & events within quantum.

🗺️ Rigetti researchers present many-to-one mapping as a solution to NISQ limitations on combinatorial optimization solvers. Plus, Classiq & QuEra are combining resources to accelerate quantum application development through resource-efficient algorithms. And while both hope and skepticism continue to abound, the steady emergence of use cases has some experts calling this the era of utility.

🗓️UPCOMING

Sunday, July 28 | QTM-X Quantum Education Series 7 of 10

📰QUANTUM QUICK BYTES

🤝 Classiq and QuEra Computing integrate technologies for optimized quantum algorithms: Classiq and QuEra Computing have just announced a collaboration to integrate QuEra’s neutral-atom quantum computers into the Classiq platform. This will allow customers to optimize quantum and hybrid quantum/classical algorithms to run on QuEra’s neutral-atom quantum technology. Features available to Classiq users now include operating on multiple qubits simultaneously and advanced qubit shuttling, while accessing Classiq’s pre-written algorithmic blocks and resource estimation tools. The goal is to encourage the creation of highly resource-efficient algorithms and ultimately accelerate quantum application development.

🔬 Real-life use cases bring life to hope that useful quantum computing is close: Industry experts have observed that recent demonstrations of real-life use cases indicate that useful quantum computing is approaching more rapidly than anticipated. Energy company Iberdrola and Multiverse Computing have used quantum computing to optimize the installation of grid-scale batteries, Japan's NTT Docomo plans to deploy quantum annealing-based technology to manage base station loads, and Rohm with Quanmatic intends to implement quantum optimization in semiconductor production. JPMorgan Chase has successfully demonstrated a quantum-secured crypto-agile network, while Pattison Food Group and D-Wave Systems achieved significant annual savings with quantum-optimized workforce scheduling. These examples highlight quantum computing's practical applications across various sectors, as noted in PwC's survey ranking it among essential emerging technologies, with 29% of companies planning investments. The era of quantum utility has begun. And on the topic of practical use case 👇️ 

✈️ Rolls-Royce partners with Tata Consultancy Services to develop hydrogen fuel systems: Rolls-Royce's development of a hydrogen fuel system for aircraft propulsion has brought Tata Consultancy Services on board for its IT expertise to address aerospace challenges. To resolve ongoing supply chain difficulties, TCS has introduced its Supply Chain Navigator platform, which uses AI to analyze both structured and unstructured data. But more interestingly (according to personal bias), TCS is also using quantum computing to help airlines manage fleet maintenance.

🌟 The rapid approach of quantum commercial relevance should instill both excitement and urgency in equal measures: Paul Terry, the CEO of Photonic, speaks on how the commercialization of quantum computing, while once considered far off, is now imminent, and that competitive advantage exists for early adopters. Historically, physics-based technologies like electromagnetism and nuclear fission have had profound impacts, and quantum computing is expected to follow. The physics of quantum properties has been studied for over a century, leading to technologies such as MRI machines and quantum sensors. The next phase focuses on superposition and entanglement, with the main challenges now being engineering and software development. As quantum computing becomes commercially relevant, organizations of all sorts would bode well to prepare for new cybersecurity models as well as explore the relevance of quantum-as-a-service offerings.

🐢 Slow and steady capital pays out in long-term gains: Quantum technology requires patient funding that supports long-term development with the full expectation that returns will not be immediate. While we have much to learn from how AI unfolded, quantum development is not on the same level today as AI is. While governments and investors have been early adopters, the main challenge is in engaging corporate end-users to secure broader adoption and ROI. The primary focus must be on creating practical value for customers to sustain the growth of the quantum sector.

🏃‍♂️ The global race for quantum technology leadership is in the hands of addressing the U.S. talent shortage: While nations world-over are heavily investing in quantum technologies, the U.S. faces a critical shortage of quantum talent. A 2024 survey by QED-C revealed that many companies struggled to meet hiring goals, with barriers such as a lack of qualified candidates, visa issues, and lengthy hiring processes. Despite government initiatives like the National Quantum Initiative, the U.S. lags in attracting international talent compared to countries with streamlined immigration processes. To ease the talent shortfall, the Department of Labor's Schedule A occupation list could be updated to include quantum-related roles and ultimately expedite permanent residency for skilled workers. QED-C will continue to collaborate with government agencies to address these challenges and ensure the U.S. remains in the quantum race.

🖥️ The University of Innsbruck and AQT have brought hybrid computation to Austria: Austria is officially hybrid computing compatible — the University of Innsbruck and the spin-off AQT have integrated a quantum computer into an HPC environment. This powerful and proven combination of quantum computing and supercomputing will be able to address complex problems in fields like chemistry, materials science, and optimization. The quantum computer itself is eco-friendly and compatible with standard 19’’ racks and room-temperature operation. The associated HPQC project will allow consortium partners to execute computations within this hybrid framework to bring additional research and innovation in quantum-aware computing to the area.

☕️FRESHLY BREWED RESEARCH

QUBIT-EFFICIENT QUANTUM COMBINATORIAL OPTIMIZATION SOLVER

QUICK BYTE: Traditional quantum optimization solvers by current qubit counts due to mapping one variable to one qubit. A qubit-efficient quantum combinatorial optimization solver is proposed — it has a many-to-one mapping by encoding classical bitstrings onto entangled wave functions, improving the scalability and effectiveness of the solver while still using current-state devices.

PRE-REQS:

• Combinatorial optimization problems require finding an optimal object in a large space of possible objects. Combinatorial optimization problems often considered for quantum computing include the Traveling Salesman Problem, the Max-cut problem, and the graph coloring problem among others.

SIGNIFICANCE: Combinatorial optimization is one of the areas in which we expect to most likely see practical examples of quantum advantage. Current approaches on quantum devices include quantum annealing, parameterized quantum algorithms with variational optimization, and recursive techniques. These rely on mapping each of the problem variables onto individual qubits and then recasting the problem as the ground state search of a Hamiltonian.

The difficulty arises because current-day devices are limited in terms of qubit quantity. While annealers can use thousands of qubits, solving real-world combinatorial optimization problems will require many thousands. While adding more qubits seems like the most obvious solution, scaling qubits also, unfortunately, scales noise. “Qubit-efficient” approaches have been proposed, such as breaking the problem into subproblems to resolve separately, but they typically lead to high computational overhead.

Researchers at Rigetti instead suggest a new strategy for mapping variables to qubits with a many-to-one relationship, where classical bitstrings are encoded as entangled wave functions. The algorithm was benchmarked and experimentally validated on Rigetti’s AnkaaTM-9Q-3 chip, providing an interim solution to combinatorial optimization solvers as we await hardware improvements.

RESULTS:

• Developed an algorithm that maps classical bitstrings to entangled wave functions to significantly reduce the number of qubits required for combinatorial optimization problems

• Demonstrated the algorithm's effectiveness through numerical benchmarks and experimental tests on Rigetti’s AnkaaTM-9Q-3 chip

• Improved the algorithm by modifying the ansatz to break the Z2 spin-flip symmetry

HONORABLE RESEARCH MENTIONS:

This paper explores how using specific knowledge about observables can improve the efficiency of quantum simulations. By focusing on families of observables, the authors propose methods to reduce errors and gate counts in both short and arbitrary-time simulations. Their advanced error analyses and numerical studies show that incorporating observable knowledge results in improved gate count estimations. —> link to Observable-Driven Speed-ups in Quantum Simulations

The principles of quantum physics and relativity are used to explore the limitations and potentials of quantum random access memory. In evaluating the scalability of QRAM, the study finds that relativistic constraints on qubits' local interactions pose challenges. Utilizing relativistic quantum field theory and Lieb-Robinson bounds, the authors establish a feasible QRAM model in hybrid quantum acoustic systems capable of supporting a large number of logical qubits. Ultimately, this elucidates the influence of relativistic causality on quantum computing hardware and the need for solutions to overcome these barriers. —> link to Fundamental causal bounds of quantum random access memories

A quantum-classical feedback protocol that applies periodic corrections based on classical computations of qubit correlations is applied to lengthen the longevity of discrete time crystal phases on NISQ devices. This approach significantly extends the survival of the many-body localized discrete time crystal phase beyond the natural decoherence time of the quantum system. —> link to Prolonging a discrete time crystal by quantum-classical feedback

UNTIL TOMORROW.